Raffaele Calogero

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Raffaele Calogero is currently Associate Professor of Molecular Biology, at the Department of Molecular Biotechnology and Health Sciences, University of Turin, Italy.[1]

Raffaele Calogero
Born
March, 03, 1960, Torino, Italy
Nationality
Italian
Education
University of Naples “Federico II” (Italy)
Fields
Bioinformatics; Molecular Biology.
Institutions
University of Naples “Federico II”, Italy (1992-1998)
University of Turin, Italy (1998-Present)
Notes
Top Italian Scientist in Biomedical Sciences [2]

Education and career

Raffaele Calogero graduated in Biological Sciences from the University of Naples “Federico II” in 1984. He spent two years (1985-1988) at Max Plank Institute fuer Mulekulare Genetic, Berlin (Germany) as research fellow. Since 1989 to 1992, he got a position a sresearch scientist at SORIN Biomedica S.p.A. (Italy). He was appointed as associated professor at University of Naples “Federico II” in 1992 and he moved to University of Turin in 1998. He is the founder of the Reproducible Bioinformatics Project[3], which is a community of developers focusing on the production of reproducible bioinformatics workflows. Since 2018, he is the representative for University of Turin at the General Assembly of Elixir Italian Node[4]. Since 2021, he is the president of the Bioinformatics Italian Society (BITS)>ref>Steering Committee :: Bioinformatics Italian Society</ref>. Since 2022, he is part of the steering committee of the FISV[5].

Research Interests

Raffaele Calogero research experience focuses on the development, optimization of bioinformatics analysis workflows and on mining transcription-based experiments, mainly in the oncology framework. An important aspect of his past and present work is the constant interest on new technologies (e.g. today single-cell omics and spatial transcriptomics) and their integration in bioinformatics analysis workflows.

Pubblications

The scientific results achieved by Raffaele Calogero are reported in over 180 peer-reviewed papers [6]. Raffaele Calogero has an H-index of 44 (according to SCOPUS[6]). Raffaele Calogero is also editor, together with Vladimir Benes, of the Book: “Single cell transcriptomics”, published by Springer in 2023[7].

Selected Publications

2: Beccuti M, Calogero RA. Single-Cell RNAseq Clustering. Methods Mol Biol. 2023;2584:241-250. doi: 10.1007/978-1-0716-2756-3_12. PMID: 36495454. (https://pubmed.ncbi.nlm.nih.gov/36495454/)

3: Alessandri L, Calogero RA. Functional-Feature-Based Data Reduction Using Sparsely Connected Autoencoders. Methods Mol Biol. 2023;2584:231-240. doi: 10.1007/978-1-0716-2756-3_11. PMID: 36495453. (https://pubmed.ncbi.nlm.nih.gov/36495453/)

4: Cordero F, Calogero RA. Single-Cell RNAseq Complexity Reduction. Methods Mol Biol. 2023;2584:217-230. doi: 10.1007/978-1-0716-2756-3_10. PMID: 36495452. (https://pubmed.ncbi.nlm.nih.gov/36495452/)

5: Olivero M, Calogero RA. Single-Cell RNAseq Data QC and Preprocessing. Methods Mol Biol. 2023;2584:205-215. doi: 10.1007/978-1-0716-2756-3_9. PMID: 36495451. (https://pubmed.ncbi.nlm.nih.gov/36495451/)

6: Avesani S, Viesi E, Alessandrì L, Motterle G, Bonnici V, Beccuti M, Calogero R, Giugno R. Stardust: improving spatial transcriptomics data analysis through space-aware modularity optimization-based clustering. Gigascience. 2022 Aug 10;11:giac075. doi: 10.1093/gigascience/giac075. PMID: 35946989; PMCID: PMC9364686. (https://pubmed.ncbi.nlm.nih.gov/35946989/)

7: Alessandri L, Ratto ML, Contaldo SG, Beccuti M, Cordero F, Arigoni M, Calogero RA. Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis. Int J Mol Sci. 2021 Nov 25;22(23):12755. doi: 10.3390/ijms222312755. PMID: 34884559; PMCID: PMC8657975. (https://pubmed.ncbi.nlm.nih.gov/34884559/)

8: Tangaro MA, Mandreoli P, Chiara M, Donvito G, Antonacci M, Parisi A, Bianco A, Romano A, Bianchi DM, Cangelosi D, Uva P, Molineris I, Nosi V, Calogero RA, Alessandri L, Pedrini E, Mordenti M, Bonetti E, Sangiorgi L, Pesole G, Zambelli F. Laniakea@ReCaS: exploring the potential of customisable Galaxy on-demand instances as a cloud-based service. BMC Bioinformatics. 2021 Nov 8;22(Suppl 15):544. doi: 10.1186/s12859-021-04401-3. PMID: 34749633; PMCID: PMC8574934. (https://pubmed.ncbi.nlm.nih.gov/34749633/)

9: Nosi V, Luca A, Milan M, Arigoni M, Benvenuti S, Cacchiarelli D, Cesana M, Riccardo S, Di Filippo L, Cordero F, Beccuti M, Comoglio PM, Calogero RA. MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning. Int J Mol Sci. 2021 Apr 19;22(8):4217. doi: 10.3390/ijms22084217. PMID: 33921709; PMCID: PMC8072630. (https://pubmed.ncbi.nlm.nih.gov/33921709/)

10: Alessandri L, Cordero F, Beccuti M, Licheri N, Arigoni M, Olivero M, Di Renzo MF, Sapino A, Calogero R. Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining. NPJ Syst Biol Appl. 2021 Jan 5;7(1):1. doi: 10.1038/s41540-020-00162-6. PMID: 33402683; PMCID: PMC7785742. (https://pubmed.ncbi.nlm.nih.gov/33402683/)

11: Alessandrì L, Cordero F, Beccuti M, Arigoni M, Calogero RA. Computational Analysis of Single-Cell RNA-Seq Data. Methods Mol Biol. 2021;2284:289-301. doi: 10.1007/978-1-0716-1307-8_16. PMID: 33835449. (https://pubmed.ncbi.nlm.nih.gov/33835449/)

12: Ferrero G, Licheri N, De Bortoli M, Calogero RA, Beccuti M, Cordero F. Computational Analysis of circRNA Expression Data. Methods Mol Biol. 2021;2284:181-192. doi: 10.1007/978-1-0716-1307-8_10. PMID: 33835443. (https://pubmed.ncbi.nlm.nih.gov/33835443/)

13: Christodoulou C, Spencer JA, Yeh SA, Turcotte R, Kokkaliaris KD, Panero R, Ramos A, Guo G, Seyedhassantehrani N, Esipova TV, Vinogradov SA, Rudzinskas S, Zhang Y, Perkins AS, Orkin SH, Calogero RA, Schroeder T, Lin CP, Camargo FD. Live-animal imaging of native haematopoietic stem and progenitor cells. Nature. 2020 Feb;578(7794):278-283. doi: 10.1038/s41586-020-1971-z. Epub 2020 Feb 5. PMID: 32025033; PMCID: PMC7021587. (https://pubmed.ncbi.nlm.nih.gov/32025033/)

14: Alessandrì L, Cordero F, Beccuti M, Arigoni M, Olivero M, Romano G, Rabellino S, Licheri N, De Libero G, Pace L, Calogero RA. rCASC: reproducible classification analysis of single-cell sequencing data. Gigascience. 2019 Sep 1;8(9):giz105. doi: 10.1093/gigascience/giz105. PMID: 31494672; PMCID: PMC6732171. (https://pubmed.ncbi.nlm.nih.gov/31494672/)

15: Bucci E, Andreev K, Björkman A, Calogero RA, Carafoli E, Carninci P, Castagnoli P, Cossarizza A, Mussini C, Guerin P, Lipworth B, Sbardella G, Stocki T, Tuosto L, van Tulleken C, Viola A. Safety and efficacy of the Russian COVID-19 vaccine: more information needed. Lancet. 2020 Oct 3;396(10256):e53. doi: 10.1016/S0140-6736(20)31960-7. Epub 2020 Sep 21. PMID: 32971041; PMCID: PMC7503114. (https://pubmed.ncbi.nlm.nih.gov/32971041/)

16: Bucci EM, Berkhof J, Gillibert A, Gopalakrishna G, Calogero RA, Bouter LM, Andreev K, Naudet F, Vlassov V. Data discrepancies and substandard reporting of interim data of Sputnik V phase 3 trial. Lancet. 2021 May 22;397(10288):1881-1883. doi: 10.1016/S0140-6736(21)00899-0. Epub 2021 May 12. PMID: 33991475; PMCID: PMC9751705. (https://pubmed.ncbi.nlm.nih.gov/33991475/)

17: Yuan WC, Pepe-Mooney B, Galli GG, Dill MT, Huang HT, Hao M, Wang Y, Liang H, Calogero RA, Camargo FD. NUAK2 is a critical YAP target in liver cancer. Nat Commun. 2018 Nov 16;9(1):4834. doi: 10.1038/s41467-018-07394-5. PMID: 30446657; PMCID: PMC6240092. (https://pubmed.ncbi.nlm.nih.gov/30446657/)

18: Kulkarni N, Alessandrì L, Panero R, Arigoni M, Olivero M, Ferrero G, Cordero F, Beccuti M, Calogero RA. Reproducible bioinformatics project: a community for reproducible bioinformatics analysis pipelines. BMC Bioinformatics. 2018 Oct 15;19(Suppl 10):349. doi: 10.1186/s12859-018-2296-x. PMID: 30367595; PMCID: PMC6191970. (https://pubmed.ncbi.nlm.nih.gov/30367595/)

19: Maglic D, Schlegelmilch K, Dost AF, Panero R, Dill MT, Calogero RA, Camargo FD. YAP-TEAD signaling promotes basal cell carcinoma development via a c-JUN/AP1 axis. EMBO J. 2018 Sep 3;37(17):e98642. doi: 10.15252/embj.201798642. Epub 2018 Jul 23. PMID: 30037824; PMCID: PMC6120663. (https://pubmed.ncbi.nlm.nih.gov/30037824/)

20: Beccuti M, Cordero F, Arigoni M, Panero R, Amparore EG, Donatelli S, Calogero RA. SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer. Bioinformatics. 2018 Mar 1;34(5):871-872. doi: 10.1093/bioinformatics/btx674. PMID: 29069297; PMCID: PMC6030956. (https://pubmed.ncbi.nlm.nih.gov/29069297/)

21: Rodriguez-Fraticelli AE, Wolock SL, Weinreb CS, Panero R, Patel SH, Jankovic M, Sun J, Calogero RA, Klein AM, Camargo FD. Clonal analysis of lineage fate in native haematopoiesis. Nature. 2018 Jan 11;553(7687):212-216. doi: 10.1038/nature25168. Epub 2018 Jan 3. PMID: 29323290; PMCID: PMC5884107. (https://pubmed.ncbi.nlm.nih.gov/29323290/)

22: Pavlasova G, Borsky M, Seda V, Cerna K, Osickova J, Doubek M, Mayer J, Calogero R, Trbusek M, Pospisilova S, Davids MS, Kipps TJ, Brown JR, Mraz M. Ibrutinib inhibits CD20 upregulation on CLL B cells mediated by the CXCR4/SDF-1 axis. Blood. 2016 Sep 22;128(12):1609-13. doi: 10.1182/blood-2016-04-709519. Epub 2016 Aug 1. PMID: 27480113; PMCID: PMC5291297. (https://pubmed.ncbi.nlm.nih.gov/27480113/)

23: Galli GG, Carrara M, Yuan WC, Valdes-Quezada C, Gurung B, Pepe-Mooney B, Zhang T, Geeven G, Gray NS, de Laat W, Calogero RA, Camargo FD. YAP Drives Growth by Controlling Transcriptional Pause Release from Dynamic Enhancers. Mol Cell. 2015 Oct 15;60(2):328-37. doi:

10.1016/j.molcel.2015.09.001. Epub 2015 Oct1. PMID: 26439301; PMCID: PMC4624327. (https://pubmed.ncbi.nlm.nih.gov/26439301/)

24: Carrara M, Lum J, Cordero F, Beccuti M, Poidinger M, Donatelli S, Calogero RA, Zolezzi F. Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis. BMC Bioinformatics. 2015;16 Suppl 9(Suppl 9):S2. doi: 10.1186/1471-2105-16-S9-S2. Epub 2015 Jun 1. PMID: 26050971; PMCID: PMC4464605. (https://pubmed.ncbi.nlm.nih.gov/26050971/)

25: D'Antonio M, D'Onorio De Meo P, Pallocca M, Picardi E, D'Erchia AM, Calogero RA, Castrignanò T, Pesole G. RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application. BMC Genomics. 2015;16(Suppl 6):S3. doi: 10.1186/1471-2164-16-S6-S3. Epub 2015 Jun 1. PMID: 26046471; PMCID: PMC4461013. (https://pubmed.ncbi.nlm.nih.gov/26046471/)

26: Beccuti M, Carrara M, Cordero F, Lazzarato F, Donatelli S, Nadalin F, Policriti A, Calogero RA. Chimera: a Bioconductor package for secondary analysis of fusion products. Bioinformatics. 2014 Dec 15;30(24):3556-7. doi: 10.1093/bioinformatics/btu662. Epub 2014 Oct 6. PMID: 25286921; PMCID: PMC4253834. (https://pubmed.ncbi.nlm.nih.gov/25286921/)

27: Tremblay AM, Missiaglia E, Galli GG, Hettmer S, Urcia R, Carrara M, Judson RN, Thway K, Nadal G, Selfe JL, Murray G, Calogero RA, De Bari C, Zammit PS, Delorenzi M, Wagers AJ, Shipley J, Wackerhage H, Camargo FD. The Hippo transducer YAP1 transforms activated satellite cells and is a potent effector of embryonal rhabdomyosarcoma formation. Cancer Cell. 2014 Aug 11;26(2):273-87. doi: 10.1016/j.ccr.2014.05.029. Epub 2014 Jul 31. PMID: 25087979. (https://pubmed.ncbi.nlm.nih.gov/25087979/)

28: Carrara M, Beccuti M, Cavallo F, Donatelli S, Lazzarato F, Cordero F, Calogero RA. State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues? BMC Bioinformatics. 2013;14 Suppl 7(Suppl 7):S2. doi: 10.1186/1471-2105-14-S7-S2. Epub 2013 Apr 22. PMID: 23815381; PMCID: PMC3633050. (https://pubmed.ncbi.nlm.nih.gov/23815381/)

References